clenspy.selection.bsel.SelectionBiasTable

class clenspy.selection.bsel.SelectionBiasTable(lam_min, lam_max, zo_low, zo_high, lob, zob, theta_lambda, b_small, b_large, damping=2.5, theta0_frac=0.5)[source]

Bases: object

b_sel plateaus per (richness bin, z_ob) row — 2 scalars per row, matching the y3_cluster_cpp wall contract (no theta grid stored).

damping/theta0_frac are one pair for the whole table (the engine that built it has one value each, not one per bin) – kept here so row() reconstructs the exact SigmoidBias the engine produced, rather than silently falling back to that class’s own defaults.

Parameters:
__init__(lam_min, lam_max, zo_low, zo_high, lob, zob, theta_lambda, b_small, b_large, damping=2.5, theta0_frac=0.5)
Parameters:
Return type:

None

Methods

__init__(lam_min, lam_max, zo_low, zo_high, ...)

from_file(path)

row(i)

to_file(path)

Attributes

damping

n_rows

theta0_frac

lam_min

lam_max

zo_low

zo_high

lob

zob

theta_lambda

b_small

b_large

lam_min: ndarray
lam_max: ndarray
zo_low: ndarray
zo_high: ndarray
lob: ndarray
zob: ndarray
theta_lambda: ndarray
b_small: ndarray
b_large: ndarray
damping: float = 2.5
theta0_frac: float = 0.5
property n_rows: int
row(i)[source]
Parameters:

i (int)

Return type:

SigmoidBias

to_file(path)[source]
Parameters:

path (str | Path)

Return type:

None

classmethod from_file(path)[source]
Parameters:

path (str | Path)

Return type:

SelectionBiasTable